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NHS
Healthcare · UK
30% fewer no-shows
NHS prevents 1,910 missed appointment slots with predictive planning
AI predicts no-shows and automatically books replacements. 1,910 extra patients seen in 6 months.
Friction
Mid and South Essex NHS Trust lost clinical capacity to missed appointments daily, with no scalable way to recover those slots.
Breakthrough
A predict-and-act workflow that forecasts no-show probability and triggers automatic back-up bookings in the same step.
Impact
30% fewer no-shows, 377 DNAs prevented, 1,910 extra patients seen in 6 months. Estimated £27.5M/year savings potential.
Unlock the full analysis with breakthrough, impact, what made it smart and its technical approach below!
Problem
Mid and South Essex NHS Foundation Trust (serving approximately 1.2 million people) struggled with missed appointments and waiting list pressure. The challenge: use clinical capacity more efficiently without adding staff.
What made it smart
Not just reminders. The system predicts who is likely not to come and sets back-up bookings to prevent empty slots. Prediction and action happen in a single automated workflow.
Technical approach
Algorithms run on anonymised appointment and patient data, enriched with external signals (weather, traffic, work patterns) to estimate no-show probability. Automation then plans alternative slots and back-up bookings. Core principle: predict and act in one workflow, via digital channels (SMS, appointment portal).
Strategic lesson
AI in healthcare creates most value when it closes the loop from signal to action, without requiring human intervention at every step.
Reflection question
In which of your processes do you currently accept a loss (empty slots, wasted capacity, missed moments) because predicting it feels too complex?